Algorithm Research & Explore
|
App. Res. of Comp. Printed Article
Vol. 40, 2023 No. 12
3655-3659,3665

Mini-batch sparse stochastic variance reduced gradient method with randomly improved Barzilai-Borwein steps

Qin Chuandong1,2
Yang Xu1
1. School of Mathematics & Information Science, North Minzu University, Yinchuan 750021, China
2. Key Laboratory of Intelligent Information & Big Data Processing, Yinchuan 750021, China
DOI: 10.19734/j.issn.1001-3695.2023.04.0177

Abstract

In order to better cope with large-scale high-dimensional sparse data sets in today's era, this paper combined the advantages of BB method, mini-batch algorithm and stochastic variance reduced gradient(SVRG), and proposed a mini-batch sparse stochastic variance reduced gradient method(MSSVRG-R2BB) with randomly improved Barzilai-Borwein step size. Firstly, on the basis of calculating the total gradient in the outer loop of SVRG, this paper added the subgradient of L1 norm, designed a sparse approximate gradient for the inner loop of SVRG, and obtained a sparse SVRG algorithm(SSVRG). On this basis, it proposed to use the improved BB method of random selection to automatically calculate and update the step size in the mini-batch sparse stochastic variance reduced gradient method, which solved the step size selection problem of the mini-batch algorithm, and expanded the MSSVRG-R2BB algorithm. Numerical experiments show that MSSVRG-R2BB algorithm can not only reduce the operation cost and reach the convergence upper bound faster, but also achieve the same optimization level of other advanced small-batch algorithms, and perform stably and well for different initial parameter selection.

Foundation Support

宁夏自然科学基金一般项目(2021AAC03230)

Publish Information

DOI: 10.19734/j.issn.1001-3695.2023.04.0177
Publish at: Application Research of Computers Printed Article, Vol. 40, 2023 No. 12
Section: Algorithm Research & Explore
Pages: 3655-3659,3665
Serial Number: 1001-3695(2023)12-020-3655-05

Publish History

[2023-07-13] Accepted Paper
[2023-12-05] Printed Article

Cite This Article

秦传东, 杨旭. 带有随机改进Barzilai-Borwein步长的小批量稀疏随机方差缩减梯度法 [J]. 计算机应用研究, 2023, 40 (12): 3655-3659,3665. (Qin Chuandong, Yang Xu. Mini-batch sparse stochastic variance reduced gradient method with randomly improved Barzilai-Borwein steps [J]. Application Research of Computers, 2023, 40 (12): 3655-3659,3665. )

About the Journal

  • Application Research of Computers Monthly Journal
  • Journal ID ISSN 1001-3695
    CN  51-1196/TP

Application Research of Computers, founded in 1984, is an academic journal of computing technology sponsored by Sichuan Institute of Computer Sciences under the Science and Technology Department of Sichuan Province.

Aiming at the urgently needed cutting-edge technology in this discipline, Application Research of Computers reflects the mainstream technology, hot technology and the latest development trend of computer application research at home and abroad in a timely manner. The main contents of the journal include high-level academic papers in this discipline, the latest scientific research results and major application results. The contents of the columns involve new theories of computer discipline, basic computer theory, algorithm theory research, algorithm design and analysis, blockchain technology, system software and software engineering technology, pattern recognition and artificial intelligence, architecture, advanced computing, parallel processing, database technology, computer network and communication technology, information security technology, computer image graphics and its latest hot application technology.

Application Research of Computers has many high-level readers and authors, and its readers are mainly senior and middle-level researchers and engineers engaged in the field of computer science, as well as teachers and students majoring in computer science and related majors in colleges and universities. Over the years, the total citation frequency and Web download rate of Application Research of Computers have been ranked among the top of similar academic journals in this discipline, and the academic papers published are highly popular among the readers for their novelty, academics, foresight, orientation and practicality.

Indexed & Evaluation

  • The Second National Periodical Award 100 Key Journals
  • Double Effect Journal of China Journal Formation
  • the Core Journal of China (Peking University 2023 Edition)
  • the Core Journal for Science
  • Chinese Science Citation Database (CSCD) Source Journals
  • RCCSE Chinese Core Academic Journals
  • Journal of China Computer Federation
  • 2020-2022 The World Journal Clout Index (WJCI) Report of Scientific and Technological Periodicals
  • Full-text Source Journal of China Science and Technology Periodicals Database
  • Source Journal of China Academic Journals Comprehensive Evaluation Database
  • Source Journals of China Academic Journals (CD-ROM Version), China Journal Network
  • 2017-2019 China Outstanding Academic Journals with International Influence (Natural Science and Engineering Technology)
  • Source Journal of Top Academic Papers (F5000) Program of China's Excellent Science and Technology Journals
  • Source Journal of China Engineering Technology Electronic Information Network and Electronic Technology Literature Database
  • Source Journal of British Science Digest (INSPEC)
  • Japan Science and Technology Agency (JST) Source Journal
  • Russian Journal of Abstracts (AJ, VINITI) Source Journals
  • Full-text Journal of EBSCO, USA
  • Cambridge Scientific Abstracts (Natural Sciences) (CSA(NS)) core journals
  • Poland Copernicus Index (IC)
  • Ulrichsweb (USA)